Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator
In this paper, we develop a new method to measure the nonlinear interactions between nonstationary time series based on the detrended cross-correlation coefficient analysis. We describe how a nonlinear interaction may be obtained by eliminating the influence of other variables on two simultaneous ti...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/7495058 |
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| _version_ | 1832553481168224256 |
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| author | Keqiang Dong Xiaojie Gao |
| author_facet | Keqiang Dong Xiaojie Gao |
| author_sort | Keqiang Dong |
| collection | DOAJ |
| description | In this paper, we develop a new method to measure the nonlinear interactions between nonstationary time series based on the detrended cross-correlation coefficient analysis. We describe how a nonlinear interaction may be obtained by eliminating the influence of other variables on two simultaneous time series. By applying two artificially generated signals, we show that the new method is working reliably for determining the cross-correlation behavior of two signals. We also illustrate the application of this method in finance and aeroengine systems. These analyses suggest that the proposed measure, derived from the detrended cross-correlation coefficient analysis, may be used to remove the influence of other variables on the cross-correlation between two simultaneous time series. |
| format | Article |
| id | doaj-art-8959dab10e1b4727a46b7aac29ce7c31 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-8959dab10e1b4727a46b7aac29ce7c312025-02-03T05:53:52ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/74950587495058Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation EstimatorKeqiang Dong0Xiaojie Gao1College of Science, Civil Aviation University of China, Tianjin 300300, ChinaCollege of Science, Civil Aviation University of China, Tianjin 300300, ChinaIn this paper, we develop a new method to measure the nonlinear interactions between nonstationary time series based on the detrended cross-correlation coefficient analysis. We describe how a nonlinear interaction may be obtained by eliminating the influence of other variables on two simultaneous time series. By applying two artificially generated signals, we show that the new method is working reliably for determining the cross-correlation behavior of two signals. We also illustrate the application of this method in finance and aeroengine systems. These analyses suggest that the proposed measure, derived from the detrended cross-correlation coefficient analysis, may be used to remove the influence of other variables on the cross-correlation between two simultaneous time series.http://dx.doi.org/10.1155/2020/7495058 |
| spellingShingle | Keqiang Dong Xiaojie Gao Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator Complexity |
| title | Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator |
| title_full | Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator |
| title_fullStr | Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator |
| title_full_unstemmed | Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator |
| title_short | Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator |
| title_sort | higher order multifractal detrended partial cross correlation analysis for the correlation estimator |
| url | http://dx.doi.org/10.1155/2020/7495058 |
| work_keys_str_mv | AT keqiangdong higherordermultifractaldetrendedpartialcrosscorrelationanalysisforthecorrelationestimator AT xiaojiegao higherordermultifractaldetrendedpartialcrosscorrelationanalysisforthecorrelationestimator |